Ingredients for a brain

In thinking about components of the brain that are important for mental function, there are several obvious things to consider. The brain's wiring diagram, embodied by the structural connectivity, is one feature. Graph theory metrics applied to anatomical networks have shown patterns that are consistent with a small-world network with dense local connections and sparser distal connections (Bullmore and Sporns, 2009). This imparts an advantage in information processing capacity compared to wiring diagrams that are either random or more regular (e.g. lattice). Studies of the brain's wiring diagram also suggest the presence of regions that act as hubs, connecting local territories of specialized processing (Hagmann et al., 2008; Honey and Sporns, 2008). On top of the anatomical architecture, to capture function one would need to consider which nodes are active at a particular time and how the sequence of activations proceeds for a given operation (McIntosh, 2004). Associated with activation is co-activation (or functional connectivity), wherein anatomical connectivity enables activity changes in one node to affect, and be affected by, others (McIntosh and Korostil, 2008). Another feature that seems less obvious in this consideration is the 'noise' that exists in these networks (Faisal et al., 2008). At one level, noise reflects the imprecision of cellular operations within an ensemble of neurons (e.g. ion channel opening and closing, membrane fluctuations). At a second level, involving connections between ensembles, variations in transmission timing affect synchrony between ensembles. Understanding the interplay of these features of noise with anatomical and functional connect-ivity may help to explain how the brain works. The importance of noise, or more generally spontaneous activity, in the brain was discussed as far back as the 1940s (Pinneo, 1966). While some researchers felt that spontaneous activity was an obstacle to be overcome for brain function (e.g. Triesman, Hebb), others considered that the internal dynamics of the brain serve an important role for consolidating memory traces and maintaining functional networks (e.g. Lashley). More recently, the wide use of functional neuroimaging to study the human brain has spawned an entire industry around studies of resting-state activity (Bartlett et al. What the brain does when it is doing nothing may seem a perverse question, but there are substantial consistencies in the observed patterns (Beckmann et al., 2005; Damoiseaux et al., 2006) that appear to have predictive power in the context of brain dysfunction (Wang et al., 2007; Greicius, 2008). While this focus on 'resting-state' …